This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
This article is part of a series about fun problems, offered with solutions. The previous one can be found here. This new problem falls in… Read More »Fun Mathematical Problem in Stochastic Geometry: Random Triangles
I am not a medical doctor, only a doctor in statistical science. Yet much of the political crisis has its origin rooted in data and… Read More »Covid: Predictions for the Next Ten Years
A hundred years of modeling didn’t help forecast the extent of the current pandemic. Hundreds of thousands of deaths could have been prevented with better… Read More »The Future of Pandemic Modeling
Summary Clustering analysis is another standard method available with SAP BW Data Mining. The clustering models based on this method may apply various combinations of… Read More »SAP BW Data Mining Analytics: Clustering Reporting (Part 4, final)
Background Every industry will be affected by algorithms and algorithmic bias. But we could rethink this as Do algorithms introduce bias or do they… Read More »Do algorithms introduce bias or do they promote transparency?
This article has been excerpted from my book, Models and Algorithms for Unlabelled Data. Next time you visit a nearby grocery store, look around inside… Read More »Equivalence class clustering and bottom-up lattice traversal (ECLAT)
What is Sentiment Analysis? Sentiment analysis can be defined as analyzing the positive or negative sentiment of the customer in text. The contextual analysis of… Read More »Applications of Sentiment Analysis
Picture Courtesy: Freepik The article explains the algorithm behind the recently introduced Python package named PyHard, based on the concept of Instance Space Analysis. It… Read More »PyHard – A tool to assess dataset quality and identify hard-to-classify instances in general
There was a time when brick-and-mortar stores were the only face of retail. The system worked well too and everyone seemed happy. That is until… Read More »Retail Predictive Analytics: Popular Use Cases
What are Non-parametric tests? Most the statistical tests are optimal under various assumptions like independence, homoscedasticity or normality. However, it might not always be possible… Read More »A Gentle Introduction to Non-Parametric Tests
